I am using S1 EW images collected over sea ice fields (i.e. S1A_EW_GRDH_1SDH_20170914T114425_20170914T114517_018371_01EEBB_B82B or S1B_EW_GRDM_1SDH_20170913T115144_20170913T115244_007373_00D02B_9C2D). Several times the backscattering is below the noise floor of the instument (that depends on the beam angle). This happens usually over standing water between ice packs.
Is there a method to get a binary “backscattering validity map” from SNAP? Just to know if the backscattering value can be consider real or is the noise of the instrument.
Would ‘S1 Thermal Noise Removal’ followed by some band math operation (e.g. zero thresholding) give you something useful?
I am not sure which values of noise are annotated in the image metadata or how SNAP’s S1 TNR operation works.
Thanks for the suggestion css. Unfortunately, I have not found a proper way to eliminate the pixel with a SNR<1 in SNAP. So I proceed in this way under Matlab:
- SAR processing (Apply orbit / Thermal noise removal/ Calibration / Reprojection)
- as described in (doi: 10.1109/TGRS.2017.2721981 sec. II-C), by using the noise equivalent backscattering curves as a function of the incidence angle I classified the image pixels.
The same curves can be found in the Sentinel-1 annual performance report.